Broadwick: A Framework for Computational Epidemiology (in java)

A. O'Hare; Samantha Lycett; Thomas Doherty; Liliana Salvaldor Monteiro Salvador; Rowland R. Kao

Broadwick: A Framework for Computational Epidemiology (in java)

A. O'Hare (Developer), Samantha Lycett (Developer), Thomas Doherty (Developer), Liliana Salvaldor Monteiro Salvador (Developer), Rowland R. Kao (Developer)

Royal (Dick) School of Veterinary Studies

Research output: Non-textual form › Software

Abstract / Description of output

Broadwick is a modular, object-oriented framework that efficiently handles large epidemiological datasets and provides packages for stochastic simulations, parameter inference using Approximate Bayesian Computation (ABC) and Markov Chain Monte Carlo (MCMC) methods.

Original language	English
Publication status	Published - 4 Feb 2016

Keywords / Materials (for Non-textual outputs)

Epidemiological modeling
EPIDEMIOLOGY
Modelling
FRAMEWORK
MODULARITY

Access to Document

http://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-0903-2

Cite this

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title = "Broadwick: A Framework for Computational Epidemiology (in java)",

abstract = "Broadwick is a modular, object-oriented framework that efficiently handles large epidemiological datasets and provides packages for stochastic simulations, parameter inference using Approximate Bayesian Computation (ABC) and Markov Chain Monte Carlo (MCMC) methods.",

keywords = "Epidemiological modeling, EPIDEMIOLOGY, Modelling, FRAMEWORK, MODULARITY",

author = "A. O'Hare and Samantha Lycett and Thomas Doherty and {Monteiro Salvador}, {Liliana Salvaldor} and Kao, {Rowland R.}",

note = "Open access source and compiled code, with tutorials accompanying publication (publication listed separately)",

year = "2016",

month = feb,

day = "4",

language = "English",

}

TY - ADVS

T1 - Broadwick

T2 - A Framework for Computational Epidemiology (in java)

A2 - O'Hare, A.

A2 - Lycett, Samantha

A2 - Doherty, Thomas

A2 - Monteiro Salvador, Liliana Salvaldor

A2 - Kao, Rowland R.

N1 - Open access source and compiled code, with tutorials accompanying publication (publication listed separately)

PY - 2016/2/4

Y1 - 2016/2/4

N2 - Broadwick is a modular, object-oriented framework that efficiently handles large epidemiological datasets and provides packages for stochastic simulations, parameter inference using Approximate Bayesian Computation (ABC) and Markov Chain Monte Carlo (MCMC) methods.

AB - Broadwick is a modular, object-oriented framework that efficiently handles large epidemiological datasets and provides packages for stochastic simulations, parameter inference using Approximate Bayesian Computation (ABC) and Markov Chain Monte Carlo (MCMC) methods.

KW - Epidemiological modeling

KW - EPIDEMIOLOGY

KW - Modelling

KW - FRAMEWORK

KW - MODULARITY

UR - http://epicscotland.github.io/broadwick.html

M3 - Software

ER -

Broadwick: A Framework for Computational Epidemiology (in java)

Abstract / Description of output

Keywords / Materials (for Non-textual outputs)

Access to Document

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Broadwick: A Framework for Computational Epidemiology

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